This research group focuses on developing robust models for analyzing complex industrial systems and monitoring operational behavior to support the implementation of best practices in preventive and corrective maintenance. Its primary research interests include condition-based maintenance, automated fault diagnosis, functional failure detection, process instrumentation, and maintenance management.

The group’s expertise encompasses process sensors, smart instrumentation, process optimization, signal processing, embedded systems, intelligent condition monitoring, digital image processing, data fusion, and data modeling. It also applies artificial intelligence and machine learning techniques to address industrial challenges and enhance system reliability and operational efficiency.